gen-table
GitHub根据SQL或自然语言描述生成数据库表结构,支持CTAS和CREATE TABLE模式,包含输入分析、DDL生成及用户确认流程。
Trigger Scenarios
Install
npx skills add Datus-ai/Datus-agent --skill gen-table -g -y
SKILL.md
Frontmatter
{
"name": "gen-table",
"tags": [
"wide-table",
"CTAS",
"DDL",
"create-table",
"query-acceleration"
],
"version": "1.0.0",
"description": "Create database tables from SQL (CTAS) or natural language descriptions",
"allowed_agents": [
"gen_table",
"gen_job"
],
"user_invocable": false,
"disable_model_invocation": false
}
CRITICAL: Interactive vs Workflow Mode
- When
ask_useris available, use it for DDL confirmation and clarification. - When
ask_useris not available (workflow, batch, or print mode), never callask_userand never wait for user input. Treat the original request as authorization only for the specific non-destructiveCREATE TABLE/ CTAS it explicitly asks for. - If critical schema details, target table, target database, or destructive authorization are missing and
ask_useris unavailable, stop and report exactly what is missing.
CRITICAL: Cancel = Immediate Stop
If the user selects "Cancel" at ANY point (any ask_user response), you MUST immediately stop ALL work. Do NOT:
- Ask follow-up questions
- Regenerate DDL
- Continue to any subsequent phase
- Propose alternatives
Return immediately with:
{"table_name": "", "output": "Cancelled by user."}
Phase 1: Analyze Input
Detect input mode:
- SQL mode: User provides a JOIN SQL or other SELECT statement → CTAS path
- Description mode: User describes table structure in natural language → CREATE TABLE path
SQL Mode (CTAS) — Go Directly to DDL
The user's SQL already fully defines the output schema. Do NOT ask the user about table usage, purpose, or column selection — the SQL is the spec.
- Parse the input SQL: Identify source tables, JOIN conditions, selected columns, and transformations.
- Call
describe_tablefor each source table to understand column types. - Optionally call
execute_sqlwithLIMIT 10to validate the query output. - Determine table name: Derive from the SQL context (e.g.,
wide_order_customer). If the user specified a name, use it. - Go directly to Phase 2 — do NOT ask about table usage, purpose, or column selection.
Description Mode (CREATE TABLE) — Confirm Schema First
Natural language is ambiguous, so clarification may be needed before generating DDL.
- Parse user description: Extract table name, columns, types, constraints.
- Call
describe_tablefor any referenced existing tables to infer column types. - If critical information is missing (e.g., no column names or types specified), clarify with
ask_userwhen available. Ifask_useris unavailable, stop and report the missing fields instead of guessing. - Go to Phase 2 once the schema is clear.
Phase 2: Generate DDL and Authorize
Generate the exact DDL SQL statement.
SQL Mode
Generate CTAS: CREATE TABLE {schema}.{table_name} AS ({select_sql})
Description Mode
Generate: CREATE TABLE {schema}.{table_name} ({column_defs})
When ask_user is available — DDL Confirmation
Call ask_user with the complete DDL embedded in the question:
ask_user(questions=[{
"question": "Generated DDL:\n\nCREATE TABLE {schema}.{table_name} AS (\n SELECT ...\n);\n\nConfirm execution?",
"options": ["Execute", "Modify", "Cancel"]
}])
Formatting rules for the question text:
- Start with a label: "Generated DDL:" or "DDL to execute:"
- Include the COMPLETE DDL statement — do NOT abbreviate or truncate
- Use
\nfor line breaks to keep the SQL readable - End with a short confirmation prompt: "Confirm execution?"
Based on user response:
- Execute: proceed to Phase 3
- Modify: ask what to change, regenerate DDL, call
ask_useragain with the updated DDL - Cancel: STOP IMMEDIATELY. Return
{"table_name": "", "output": "Cancelled by user."}. Do NOT continue.
When ask_user is unavailable — Workflow Authorization
- Do not call
ask_user. - Proceed to Phase 3 only when the request explicitly asks to create this table or CTAS result and the target database/table is unambiguous.
- If the target table already exists, proceed only if the request explicitly authorizes replacement, overwrite, drop/recreate, or equivalent destructive behavior.
- If the DDL includes
DROP,ALTER,TRUNCATE,CREATE OR REPLACE, or any existing-object replacement, require explicit authorization in the original request. Otherwise stop and report the required authorization. - Include the final DDL in the output summary so the caller can audit what was executed.
Phase 3: Execute and Verify
- Call
execute_sql(sql)with the confirmed or workflow-authorized DDL statement. - Verify:
- SQL Mode: Call
execute_sql("SELECT COUNT(*) FROM {schema}.{table_name}")to confirm row count - Description Mode: Call
describe_table("{schema}.{table_name}")to confirm schema matches
- SQL Mode: Call
- Call
describe_table("{schema}.{table_name}")to confirm the created schema.
If DDL fails:
- Parse the error message
- If
ask_useris available, fix the SQL, show the updated DDL to the user viaask_user, and retry (up to 3 attempts) - If
ask_useris unavailable, fix and retry directly up to 3 attempts when the intent remains the same and no new destructive action is introduced - If still failing, report the final error and the last attempted DDL in the output
Phase 4: Summary
Output a summary including:
- Created table name and location
- Row count (for CTAS) or column count (for CREATE TABLE)
- Column list with types
- Original SQL (for CTAS) or user description (for CREATE TABLE)
- Hint: if the user needs a semantic model and the project uses Dosi, suggest
task(type="semantic_modeling", prompt="{table_name}"). For MetricFlow or OSI, explain that the project is query-only and must be migrated to Dosi before authoring.
Important Rules
- Use
ask_userbefore executing DDL only when the tool is available. - In workflow mode, execute only explicitly requested non-destructive table creation; block ambiguous or destructive work instead of guessing.
- DDL is irreversible — always include the exact DDL SQL in
ask_userconfirmation when interactive, or in the final output when workflow mode executes. - If the target table already exists, ask whether to drop/recreate/abort when interactive; require explicit replacement authorization when workflow mode.
- Language: match user's language (Chinese input → Chinese output)
- Do NOT modify the source tables — only create new tables
- Single responsibility — gen-table only creates tables and does not generate semantic model YAML. In a Dosi project, suggest
semantic_modelingfor semantic authoring; in MetricFlow or OSI, give the query-only migration guidance instead.
Version History
- 8fb79f6 Current 2026-08-20 12:34


